{"id":"W3016195942","doi":"10.1007/s11625-020-00789-8","title":"Environmental justice and the SDGs: from synergies to gaps and contradictions","year":2020,"lang":"en","type":"article","venue":"Sustainability Science","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":385,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"University of Sussex","keywords":"Environmental justice; Sustainable development; Sociology; Environmental ethics; Transformative learning; Degrowth; Environmental studies; Nexus (standard); Poverty; Economic Justice; Mainstream; Sustainability; Wicked problem; Political science; Economics; Ecology; Law; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0009400765,0.00008196168,0.0001223784,0.00002369308,0.002268319,0.0001746274,0.0002594596,0.00003255922,0.00005358155],"category_scores_gemma":[0.001716535,0.00006389729,0.00001801778,0.0002278584,0.006322566,0.0004250026,0.0002086146,0.0001185462,0.000008341891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002351012,"about_ca_system_score_gemma":0.0002303122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002705327,"about_ca_topic_score_gemma":0.000496419,"domain_scores_codex":[0.9985986,0.0001438175,0.0001423781,0.000363801,0.0003839216,0.0003674319],"domain_scores_gemma":[0.998889,0.0005110832,0.00003244386,0.0001405912,0.00002129307,0.0004055624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002661259,0.00009928588,0.07281812,0.0004476245,0.00001247924,0.00000875056,0.553745,0.0001360673,0.0004849933,0.362324,0.000667592,0.00898996],"study_design_scores_gemma":[0.0004438311,0.00006794533,0.2594824,0.00001155217,0.00008417336,5.78606e-7,0.7142342,0.0003212822,0.00002974225,0.009548187,0.01562869,0.0001474252],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9096288,0.001402888,0.0001622298,0.08665719,0.00009337258,0.0005898954,0.00002379755,0.00003265749,0.001409145],"genre_scores_gemma":[0.993154,0.001050397,0.0001599946,0.0054169,0.0001123705,0.00002632527,5.332542e-7,0.000003178917,0.00007624822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3527758,"threshold_uncertainty_score":0.9990306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01106791716780117,"score_gpt":0.2846646605235035,"score_spread":0.2735967433557024,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}